@@ -329,13 +329,18 @@ def _get_counts_nanvar(mask, axis, ddof):
329 329
return count, d
330 330 331 331 332 -
@disallow('M8')
332 +
@disallow('M8','m8')
333 333
@bottleneck_switch(ddof=1)
334 334
def nanvar(values, axis=None, skipna=True, ddof=1):
335 -
if not _is_floating_dtype(values):
336 -
values = values.astype('f8')
335 + 336 +
# we are going to allow timedelta64[ns] here
337 +
# but NOT going to coerce them to the Timedelta type
338 +
# as this could cause overflow
339 +
# so var cannot be computed (but std can!)
337 340 338 341
mask = isnull(values)
342 +
if not _is_floating_dtype(values):
343 +
values = values.astype('f8')
339 344 340 345
count, d = _get_counts_nanvar(mask, axis, ddof)
341 346
@@ -347,13 +352,13 @@ def nanvar(values, axis=None, skipna=True, ddof=1):
347 352
XX = _ensure_numeric((values ** 2).sum(axis))
348 353
return np.fabs((XX - X ** 2 / count) / d)
349 354 350 - 355 +
@disallow('M8','m8')
351 356
def nansem(values, axis=None, skipna=True, ddof=1):
352 357
var = nanvar(values, axis, skipna, ddof=ddof)
353 358 359 +
mask = isnull(values)
354 360
if not _is_floating_dtype(values):
355 361
values = values.astype('f8')
356 -
mask = isnull(values)
357 362
count, _ = _get_counts_nanvar(mask, axis, ddof)
358 363 359 364
return np.sqrt(var)/np.sqrt(count)
@@ -442,12 +447,13 @@ def nanargmin(values, axis=None, skipna=True):
442 447
return result
443 448 444 449 445 -
@disallow('M8')
450 +
@disallow('M8','m8')
446 451
def nanskew(values, axis=None, skipna=True):
452 + 453 +
mask = isnull(values)
447 454
if not _is_floating_dtype(values):
448 455
values = values.astype('f8')
449 456 450 -
mask = isnull(values)
451 457
count = _get_counts(mask, axis)
452 458 453 459
if skipna:
@@ -476,12 +482,13 @@ def nanskew(values, axis=None, skipna=True):
476 482
return result
477 483 478 484 479 -
@disallow('M8')
485 +
@disallow('M8','m8')
480 486
def nankurt(values, axis=None, skipna=True):
487 + 488 +
mask = isnull(values)
481 489
if not _is_floating_dtype(values):
482 490
values = values.astype('f8')
483 491 484 -
mask = isnull(values)
485 492
count = _get_counts(mask, axis)
486 493 487 494
if skipna:
@@ -574,7 +581,7 @@ def _zero_out_fperr(arg):
574 581
return 0 if np.abs(arg) < 1e-14 else arg
575 582 576 583 577 -
@disallow('M8')
584 +
@disallow('M8','m8')
578 585
def nancorr(a, b, method='pearson', min_periods=None):
579 586
"""
580 587
a, b: ndarrays
@@ -621,7 +628,7 @@ def _spearman(a, b):
621 628
return _cor_methods[method]
622 629 623 630 624 -
@disallow('M8')
631 +
@disallow('M8','m8')
625 632
def nancov(a, b, min_periods=None):
626 633
if len(a) != len(b):
627 634
raise AssertionError('Operands to nancov must have same size')
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